DIGESuite: a Cytoscape plug-in for 2D-DIGE analysis

TALESNIK, SERGIO; MISHIMA. JUAN; CRISTÓBAL FRESNO; RIBERO GABRIELA; MERINO, GABRIELA; PRATO, LAURA; LLERA, ANDREA SABINA; FERNÁNDEZ, ELMER ANDRÉS

Oro Verde

Congreso; 3er Congreso Argentino de Bioinformatica y Biologia Computacional; 2012

A2B2C

Background: biomedical companies usually offer proprietary black-box software associated with their machinery. In this context, the user cannot check whether the data cope with model assumptions, in order to apply alternative approaches. Furthermore, user-interfaces are very restricted not allowing the user to extend the analysis. This is not the exception in GE Healthcare software Decyder® for two-dimensional difference gel electrophoresis (2D-DIGE) [1]; where a global view of the state of a proteome can be obtained, by the examination of up to three labeled samples on a two-dimensional gel. The aim of this technology is the detection of spots (with a priori unknown proteins), showing a statistical expression difference under different experimental conditions. In this context, is crucial to include proper visualization during pre-processing steps such as spot filtering and normalization, prior to differential expression analysis. To overcome these limitations we propose DIGESuite, a plug-in for 2D-DIGE protein expression analysis, to extend the well-known bioinformatics? flexible visualization tool Cytoscape [2]. Methods: the plug-in uses a client-server topology, where Cytoscape offers the graphical front end and the statistical engine R [3] works as back-end. Decyder® raw/normalized volume images data files are displayed for each gel image using Cytoscape capabilities (see Figure 1). The user can easily filter problematic spots (saturated or dusty ones), check for protein spots distribution using boxplots and use normalization alternatives such as two-stage linear mixed models [4]. Even if necessary, the user can open an R terminal to tune the data at his will. Once normalized, a user friendly interface lets the user specified the linear or mixed model for differential expression analysis instead of Decyder® one/two way ANOVA. Automatically, differentially expressed spots are highlighted in the gel, according to user significance threshold (raw/adjusted p-values and/or fold-change). It also provides a complete report of the processed steps applied, as well as the location of the spots to pick from MS protein identification. Furthermore, additional Cytoscape plug-ins can be included in the analysis according to the user?s needs. Conclusion: as far as we know, there is no available free tool that allows the analysis of protein data in a consistent and flexible manner. DIGESuite can be used after Decyder® image analysis has been carried, allowing flexible filtering, normalization, differential expression analysis and spot information for MS protein identification. This tool can also be used jointly with other Cytoscape plug-ins to further extend protein expression analysis.